Gregg Siegal

2.8k total citations
59 papers, 2.2k citations indexed

About

Gregg Siegal is a scholar working on Molecular Biology, Computational Theory and Mathematics and Cellular and Molecular Neuroscience. According to data from OpenAlex, Gregg Siegal has authored 59 papers receiving a total of 2.2k indexed citations (citations by other indexed papers that have themselves been cited), including 55 papers in Molecular Biology, 9 papers in Computational Theory and Mathematics and 7 papers in Cellular and Molecular Neuroscience. Recurrent topics in Gregg Siegal's work include Protein Structure and Dynamics (15 papers), Computational Drug Discovery Methods (9 papers) and Protein Kinase Regulation and GTPase Signaling (7 papers). Gregg Siegal is often cited by papers focused on Protein Structure and Dynamics (15 papers), Computational Drug Discovery Methods (9 papers) and Protein Kinase Regulation and GTPase Signaling (7 papers). Gregg Siegal collaborates with scholars based in Netherlands, United States and United Kingdom. Gregg Siegal's co-authors include Eiso AB, Adriaan P. IJzerman, Johan G. Hollander, Jan Schultz, Harald Schwalbe, Robert A. Bambara, John J. Turchi, Fiona H. Marshall, Philipp Selenko and Horst Kessler and has published in prestigious journals such as Chemical Reviews, Proceedings of the National Academy of Sciences and Journal of the American Chemical Society.

In The Last Decade

Gregg Siegal

59 papers receiving 2.1k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Gregg Siegal Netherlands 27 1.7k 355 305 284 278 59 2.2k
M. Sundström Sweden 23 2.4k 1.4× 255 0.7× 293 1.0× 201 0.7× 200 0.7× 40 3.4k
Andrew A. Bogan United States 6 1.9k 1.1× 379 1.1× 432 1.4× 114 0.4× 328 1.2× 8 2.3k
Alexander L. Breeze United Kingdom 27 1.8k 1.1× 270 0.8× 227 0.7× 119 0.4× 153 0.6× 48 2.2k
Maria M. Flocco Italy 21 1.4k 0.8× 270 0.8× 366 1.2× 211 0.7× 100 0.4× 27 1.8k
Kannan Gunasekaran United States 24 2.5k 1.4× 283 0.8× 730 2.4× 226 0.8× 487 1.8× 39 2.9k
Christopher L. McClendon United States 18 2.2k 1.3× 604 1.7× 384 1.3× 165 0.6× 293 1.1× 25 2.7k
M. Stihle Switzerland 23 1.7k 1.0× 242 0.7× 324 1.1× 192 0.7× 515 1.9× 29 2.8k
Jennifer L. Miller United States 21 1.5k 0.9× 207 0.6× 207 0.7× 152 0.5× 109 0.4× 33 2.1k
Georgios Archontis Cyprus 26 1.6k 0.9× 170 0.5× 445 1.5× 176 0.6× 138 0.5× 53 2.3k

Countries citing papers authored by Gregg Siegal

Since Specialization
Citations

This map shows the geographic impact of Gregg Siegal's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Gregg Siegal with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Gregg Siegal more than expected).

Fields of papers citing papers by Gregg Siegal

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Gregg Siegal. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Gregg Siegal. The network helps show where Gregg Siegal may publish in the future.

Co-authorship network of co-authors of Gregg Siegal

This figure shows the co-authorship network connecting the top 25 collaborators of Gregg Siegal. A scholar is included among the top collaborators of Gregg Siegal based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Gregg Siegal. Gregg Siegal is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Hollander, Johan G., et al.. (2020). NMR in target driven drug discovery: why not?. Journal of Biomolecular NMR. 74(10-11). 521–529. 11 indexed citations
2.
Siegal, Gregg, et al.. (2020). 1H, 13C, 15N backbone and IVL methyl group resonance assignment of the fungal β-glucosidase from Trichoderma reesei. Biomolecular NMR Assignments. 14(2). 265–268. 1 indexed citations
3.
Siegal, Gregg & Philipp Selenko. (2019). Cells, drugs and NMR. Journal of Magnetic Resonance. 306. 202–212. 48 indexed citations
4.
Congreve, Miles, et al.. (2011). Fragment Screening of Stabilized G-Protein-Coupled Receptors Using Biophysical Methods. Methods in enzymology on CD-ROM/Methods in enzymology. 493. 115–136. 86 indexed citations
5.
Jansen, Jacob G., et al.. (2011). The Rev1 translesion synthesis polymerase has multiple distinct DNA binding modes. DNA repair. 10(9). 915–925. 33 indexed citations
6.
Overmeer, René, Audrey M. Gourdin, Giuseppina Giglia‐Mari, et al.. (2010). Replication Factor C Recruits DNA Polymerase δ to Sites of Nucleotide Excision Repair but Is Not Required for PCNA Recruitment. Molecular and Cellular Biology. 30(20). 4828–4839. 49 indexed citations
7.
Kobayashi, Masakazu, Eiso AB, Alexandre M. J. J. Bonvin, & Gregg Siegal. (2010). Structure of the DNA-bound BRCA1 C-terminal Region from Human Replication Factor C p140 and Model of the Protein-DNA Complex. Journal of Biological Chemistry. 285(13). 10087–10097. 28 indexed citations
8.
Zhou, Yunpeng, Dan Chen, Eiso AB, et al.. (2010). Application of Fragment-Based Drug Discovery to Membrane Proteins: Identification of Ligands of the Integral Membrane Enzyme DsbB. Chemistry & Biology. 17(8). 881–891. 57 indexed citations
9.
Siegal, Gregg & Johan G. Hollander. (2009). Target Immobilization and NMR Screening of Fragments in Early Drug Discovery. Current Topics in Medicinal Chemistry. 9(18). 1736–1745. 10 indexed citations
10.
Marquardsen, Thorsten, Martin Hofmann, Johan G. Hollander, et al.. (2006). Development of a dual cell, flow-injection sample holder, and NMR probe for comparative ligand-binding studies. Journal of Magnetic Resonance. 182(1). 55–65. 18 indexed citations
11.
Vanwetswinkel, Sophie, John van Duynhoven, Johan G. Hollander, et al.. (2005). TINS, Target Immobilized NMR Screening: An Efficient and Sensitive Method for Ligand Discovery. Chemistry & Biology. 12(2). 207–216. 107 indexed citations
12.
Vanwetswinkel, Sophie, G.R. Andersen, Peter Güntert, et al.. (2003). Solution Structure of the 162 Residue C-terminal Domain of Human Elongation Factor 1Bγ. Journal of Biological Chemistry. 278(44). 43443–43451. 13 indexed citations
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Siegal, Gregg, et al.. (1999). Crystal structure of the C-terminal SH2 domain of the p85α regulatory subunit of phosphoinositide 3-kinase: an SH2 domain mimicking its own substrate. Journal of Molecular Biology. 292(4). 763–770. 26 indexed citations
16.
Siegal, Gregg, Ben Davis, Søren M. Kristensen, et al.. (1998). Solution structure of the C-terminal SH2 domain of the p85α regulatory subunit of phosphoinositide 3-kinase 1 1Edited by P. E. Wright. Journal of Molecular Biology. 276(2). 461–478. 48 indexed citations
17.
Dijk, Jan, W. Möller, Gregg Siegal, et al.. (1998). 1H, 15N and 13C chemical shift assignment of the guanine nucleotide exchange domain of human Elongation Factor-one beta. Journal of Biomolecular NMR. 12(3). 467–468. 1 indexed citations
18.
Barnes, Mack N., Jessy S. Deshane, Gregg Siegal, Ronald D. Alvarez, & D T Curiel. (1996). Novel gene therapy strategy to accomplish growth factor modulation induces enhanced tumor cell chemosensitivity.. PubMed. 2(7). 1089–95. 20 indexed citations
19.
Pervushin, Konstantin, Martin Billeter, Gregg Siegal, & Kurt Wüthrich. (1996). Structural Role of a Buried Salt Bridge in the 434 Repressor DNA-binding Domain. Journal of Molecular Biology. 264(5). 1002–1012. 42 indexed citations
20.
Wilson, Kim, Gregg Siegal, & Edith M. Lord. (1989). Tumor necrosis factor-mediated cytotoxicity by tumor-associated macrophages. Cellular Immunology. 123(1). 158–165. 10 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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